“It was kind of like flipping a coin, whether the human reviewers could actually address policies correctly, and this was many days after the harm had already occurred anyway,” Levenson told TechCrunch.

That sort of delayed, reactive approach is not sustainable in a world of nimble and well-funded adversarial actors. The rise of AI chatbots has only compounded the problem, as content moderation failures have resulted in a string of high-profile incidents, like chatbots providing teens with self-harm guidance or AI-generated imagery evading safety filters.

Levenson’s frustration led to the idea of “policy as code” — a way to turn static policy documents into executable, updatable logic tightly coupled to enforcement. That insight led to the founding of Moonbounce, which announced on Friday it has raised $12 million in funding, TechCrunch has exclusively learned. The round was co-led by Amplify Partners and StepStone Group.

Moonbounce works with companies to provide an additional safety layer wherever content is generated, whether by a user or by AI. The company has trained its own large language model to look at a customer’s policy documents, evaluate content at runtime, provide a response in 300 milliseconds or less, and take action. Depending on customer preference, that action could look like Moonbounce’s system slowing down distribution while the content awaits a human review later, or it might block high-risk content in the moment.